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Hello, man.
First of all. I want to say thank you. Thank you for your brilliant article, which showed me a lot of interesting things in imbalanced ML - https://medium.com/data-science-at-microsoft/…
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In order to solve the problem of unbalanced categories and difficult samples
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### Use case
common
### Name of resource
SMOTE dataset balancing
### ID
SMOTE_dataset_balancing
### Description
Dataset balancing using SMOTE oversampling technique. A balanced da…
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Hi!
I have a binary classification dataset with highly imbalanced label distributions (pos : neg == 1 : 200)
I was trying to apply the BERT code in [Neural Network Quick Start Tutorial](https://…
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I find the InfoGain loss layer that is now available in caffe (https://github.com/BVLC/caffe/pull/3855 ) very useful for my multi-class classification application with highly imbalanced data distribut…
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Hi,
Per https://arxiv.org/pdf/1802.01021.pdf Table 1, the tested accuracy is 0.98. The model generated using the provided systems: typeclassifier has a F1 score of .88
cmd: python3 learning/train_…
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### Question
Hi,
I use yolov5x with this setting (train: 70%, val: 10%, test: 20%)
```
train: images/train # train images (relative to 'path') 128 images
val: images/val # val images (relativ…
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This is my setup for transfer learning:
- model: `google/vit-base-patch16-224`: this is the most downloaded and well-known base transformer model.
- dataset: `oxford-iiit pets dataset`: [hf-link](…
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Will it possible for you to add a description the model you're using? Especially which cost function you used for multi-label classification. If possible, please also provide some accuracy measure on …
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https://liamwang666.github.io/2019/11/30/%E8%AE%BA%E6%96%87%E9%98%85%E8%AF%BB%E7%AC%94%E8%AE%B01%E3%80%8AClassification-on-Imbalanced-Data-Sets-Taking-Advantage-of-Errors-to-Improve-Performance%E3%80%…